Edge Pixel Specification in Halftone Images Using Component Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image processing techniques fail to accurately specify edge pixels in images containing halftone dots, leading to incorrect detection of edges in uniform areas.
Innovation Solution
An image processing apparatus that acquires target image data, smooths component images using a Gaussian filter, enhances edges, and generates single-component image data to effectively specify edge pixels while suppressing edge detection caused by halftone dots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge detection techniques (Sobel filter) are applied to scan images, then edge pixels can be specified, but halftone dots in uniform areas are incorrectly detected as edge pixels
Solution Approach 1:
The image is segmented into multiple color component images (C, M, Y, K), and edge detection is performed separately on each component. This segmentation allows the system to distinguish between genuine edges and halftone dot patterns by analyzing edge characteristics across different color channels, thereby improving edge pixel specification accuracy while suppressing halftone dot interference.
Solution Approach 2:
The patent introduces an intermediary processing step where edge-detected images from multiple color components are combined and processed further. This intermediary stage includes operations such as logical OR combination of edge images, noise filtering, and morphological operations that serve as mediators to separate true edges from halftone dot artifacts before final edge pixel specification.
2Measurement precision
If multiple color component images are processed for edge detection, then edge pixel specification accuracy improves, but processing complexity increases
Solution Approach 1:
The patent merges the processing of multiple color component images by combining their edge-detected results through logical operations (such as OR combination). This merging approach consolidates the information from C, M, Y, and K components into a unified edge map, improving accuracy while managing complexity through efficient combination operations rather than independent processing of each component throughout the entire pipeline.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables accurate edge pixel specification, reducing the appearance of moire patterns and improving the printed image quality by distinguishing between edge and non-edge pixels in images with halftone dots.
Implementation Method 1
smoothing the plurality of component images to generate respective sets of a plurality of sets of smoothed component image data
Implementation Method 2
enhancing an edge in each of the plurality of smoothed component images to generate corresponding one set of a plurality of sets of enhanced component image data
Data Source
AI summary
An image processing apparatus performs: acquiring target image data representing a target image including a plurality of pixels, the target image data including a plurality of sets of component image data representing respective ones of a plurality of component images; smoothing the plurality of component images to generate respective sets of a plurality of sets of smoothed component image data representing respective ones of a plurality of smoothed component images; enhancing an edge in each of the plurality of smoothed component images to generate corresponding one set of a plurality of sets of enhanced component image data; generating single-component image data including one type of component value corresponding to each of the plurality of pixels by using the plurality of sets of enhanced component image data; and specifying a plurality of edge pixels using the single-component image data, the plurality of edge pixels constituting an edge in the target image.